The Analytics of Risk Model Validation

The Analytics of Risk Model Validation
Author: George A. Christodoulakis,Stephen Satchell
Publsiher: Elsevier
Total Pages: 216
Release: 2007-11-14
ISBN 10: 9780080553887
ISBN 13: 0080553885
Language: EN, FR, DE, ES & NL

The Analytics of Risk Model Validation Book Review:

Risk model validation is an emerging and important area of research, and has arisen because of Basel I and II. These regulatory initiatives require trading institutions and lending institutions to compute their reserve capital in a highly analytic way, based on the use of internal risk models. It is part of the regulatory structure that these risk models be validated both internally and externally, and there is a great shortage of information as to best practise. Editors Christodoulakis and Satchell collect papers that are beginning to appear by regulators, consultants, and academics, to provide the first collection that focuses on the quantitative side of model validation. The book covers the three main areas of risk: Credit Risk and Market and Operational Risk. *Risk model validation is a requirement of Basel I and II *The first collection of papers in this new and developing area of research *International authors cover model validation in credit, market, and operational risk

The Validation of Risk Models

The Validation of Risk Models
Author: S. Scandizzo
Publsiher: Palgrave Macmillan
Total Pages: 242
Release: 2016-04-27
ISBN 10: 9781137436955
ISBN 13: 1137436956
Language: EN, FR, DE, ES & NL

The Validation of Risk Models Book Review:

The practice of quantitative risk management has reached unprecedented levels of refinement. The pricing, the assessment of risk as well as the computation of the capital requirements for highly complex transactions are performed through equally complex mathematical models, running on advanced computer systems, developed and operated by dedicated, highly qualified specialists. With this sophistication, however, come risks that are unpredictable, globally challenging and difficult to manage. Model risk is a prime example and precisely the kind of risk that those tasked with managing financial institutions as well as those overseeing the soundness and stability of the financial system should worry about. This book starts with setting the problem of the validation of risk models within the context of banking governance and proposes a comprehensive methodological framework for the assessment of models against compliance, qualitative and quantitative benchmarks. It provides a comprehensive guide to the tools and techniques required for the qualitative and quantitative validation of the key categories of risk models, and introduces a practical methodology for the measurement of the resulting model risk and its translation into prudent adjustments to capital requirements and other estimates.

Credit Risk Analytics

Credit Risk Analytics
Author: Bart Baesens,Daniel Roesch,Harald Scheule
Publsiher: John Wiley & Sons
Total Pages: 512
Release: 2016-10-03
ISBN 10: 1119143985
ISBN 13: 9781119143987
Language: EN, FR, DE, ES & NL

Credit Risk Analytics Book Review:

The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. Understand the general concepts of credit risk management Validate and stress-test existing models Access working examples based on both real and simulated data Learn useful code for implementing and validating models in SAS Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process.

IFRS 9 and CECL Credit Risk Modelling and Validation

IFRS 9 and CECL Credit Risk Modelling and Validation
Author: Tiziano Bellini
Publsiher: Academic Press
Total Pages: 316
Release: 2019-02-08
ISBN 10: 012814940X
ISBN 13: 9780128149409
Language: EN, FR, DE, ES & NL

IFRS 9 and CECL Credit Risk Modelling and Validation Book Review:

IFRS 9 and CECL Credit Risk Modelling and Validation covers a hot topic in risk management. Both IFRS 9 and CECL accounting standards require Banks to adopt a new perspective in assessing Expected Credit Losses. The book explores a wide range of models and corresponding validation procedures. The most traditional regression analyses pave the way to more innovative methods like machine learning, survival analysis, and competing risk modelling. Special attention is then devoted to scarce data and low default portfolios. A practical approach inspires the learning journey. In each section the theoretical dissertation is accompanied by Examples and Case Studies worked in R and SAS, the most widely used software packages used by practitioners in Credit Risk Management. Offers a broad survey that explains which models work best for mortgage, small business, cards, commercial real estate, commercial loans and other credit products Concentrates on specific aspects of the modelling process by focusing on lifetime estimates Provides an hands-on approach to enable readers to perform model development, validation and audit of credit risk models

Understanding and Managing Model Risk

Understanding and Managing Model Risk
Author: Massimo Morini
Publsiher: John Wiley & Sons
Total Pages: 352
Release: 2011-10-20
ISBN 10: 0470977744
ISBN 13: 9780470977743
Language: EN, FR, DE, ES & NL

Understanding and Managing Model Risk Book Review:

A guide to the validation and risk management of quantitative models used for pricing and hedging Whereas the majority of quantitative finance books focus on mathematics and risk management books focus on regulatory aspects, this book addresses the elements missed by this literature--the risks of the models themselves. This book starts from regulatory issues, but translates them into practical suggestions to reduce the likelihood of model losses, basing model risk and validation on market experience and on a wide range of real-world examples, with a high level of detail and precise operative indications.

The Validation of Risk Models

The Validation of Risk Models
Author: S. Scandizzo
Publsiher: Springer
Total Pages: 242
Release: 2016-07-01
ISBN 10: 1137436964
ISBN 13: 9781137436962
Language: EN, FR, DE, ES & NL

The Validation of Risk Models Book Review:

This book is a one-stop-shop reference for risk management practitioners involved in the validation of risk models. It is a comprehensive manual about the tools, techniques and processes to be followed, focused on all the models that are relevant in the capital requirements and supervisory review of large international banks.

Credit Risk Model Validation and Monitoring Methods

Credit Risk Model Validation and Monitoring Methods
Author: Sunil Verma
Publsiher: Unknown
Total Pages: 288
Release: 2008-02-28
ISBN 10: 9780470756249
ISBN 13: 0470756241
Language: EN, FR, DE, ES & NL

Credit Risk Model Validation and Monitoring Methods Book Review:

* Credit Risk Model Validation and Monitoring Methods provides a one-stop guide to the latest validation and monitoring techniques.

The Basel II Risk Parameters

The Basel II Risk Parameters
Author: Bernd Engelmann,Robert Rauhmeier
Publsiher: Springer Science & Business Media
Total Pages: 426
Release: 2011-03-31
ISBN 10: 9783642161148
ISBN 13: 3642161146
Language: EN, FR, DE, ES & NL

The Basel II Risk Parameters Book Review:

The estimation and the validation of the Basel II risk parameters PD (default probability), LGD (loss given fault), and EAD (exposure at default) is an important problem in banking practice. These parameters are used on the one hand as inputs to credit portfolio models and in loan pricing frameworks, on the other to compute regulatory capital according to the new Basel rules. This book covers the state-of-the-art in designing and validating rating systems and default probability estimations. Furthermore, it presents techniques to estimate LGD and EAD and includes a chapter on stress testing of the Basel II risk parameters. The second edition is extended by three chapters explaining how the Basel II risk parameters can be used for building a framework for risk-adjusted pricing and risk management of loans.

Risk Model Validation

Risk Model Validation
Author: Peter Quell
Publsiher: Unknown
Total Pages: 329
Release: 2016
ISBN 10: 9781782722632
ISBN 13: 1782722637
Language: EN, FR, DE, ES & NL

Risk Model Validation Book Review:

Credit Risk Scorecards

Credit Risk Scorecards
Author: Naeem Siddiqi
Publsiher: John Wiley & Sons
Total Pages: 208
Release: 2012-06-29
ISBN 10: 1118429168
ISBN 13: 9781118429167
Language: EN, FR, DE, ES & NL

Credit Risk Scorecards Book Review:

Praise for Credit Risk Scorecards "Scorecard development is important to retail financial services in terms of credit risk management, Basel II compliance, and marketing of credit products. Credit Risk Scorecards provides insight into professional practices in different stages of credit scorecard development, such as model building, validation, and implementation. The book should be compulsory reading for modern credit risk managers." —Michael C. S. Wong Associate Professor of Finance, City University of Hong Kong Hong Kong Regional Director, Global Association of Risk Professionals "Siddiqi offers a practical, step-by-step guide for developing and implementing successful credit scorecards. He relays the key steps in an ordered and simple-to-follow fashion. A 'must read' for anyone managing the development of a scorecard." —Jonathan G. Baum Chief Risk Officer, GE Consumer Finance, Europe "A comprehensive guide, not only for scorecard specialists but for all consumer credit professionals. The book provides the A-to-Z of scorecard development, implementation, and monitoring processes. This is an important read for all consumer-lending practitioners." —Satinder Ahluwalia Vice President and Head-Retail Credit, Mashreqbank, UAE "This practical text provides a strong foundation in the technical issues involved in building credit scoring models. This book will become required reading for all those working in this area." —J. Michael Hardin, PhD Professor of StatisticsDepartment of Information Systems, Statistics, and Management ScienceDirector, Institute of Business Intelligence "Mr. Siddiqi has captured the true essence of the credit risk practitioner's primary tool, the predictive scorecard. He has combined both art and science in demonstrating the critical advantages that scorecards achieve when employed in marketing, acquisition, account management, and recoveries. This text should be part of every risk manager's library." —Stephen D. Morris Director, Credit Risk, ING Bank of Canada

Credit Risk Analytics

Credit Risk Analytics
Author: Harald Scheule
Publsiher: Createspace Independent Publishing Platform
Total Pages: 264
Release: 2017-11-23
ISBN 10: 9781977760869
ISBN 13: 1977760864
Language: EN, FR, DE, ES & NL

Credit Risk Analytics Book Review:

Credit risk analytics in R will enable you to build credit risk models from start to finish. Accessing real credit data via the accompanying website www.creditriskanalytics.net, you will master a wide range of applications, including building your own PD, LGD and EAD models as well as mastering industry challenges such as reject inference, low default portfolio risk modeling, model validation and stress testing. This book has been written as a companion to Baesens, B., Roesch, D. and Scheule, H., 2016. Credit Risk Analytics: Measurement Techniques, Applications, and Examples in SAS. John Wiley & Sons.

Clinical Prediction Models

Clinical Prediction Models
Author: Ewout W. Steyerberg
Publsiher: Springer Science & Business Media
Total Pages: 500
Release: 2008-12-16
ISBN 10: 9780387772448
ISBN 13: 0387772448
Language: EN, FR, DE, ES & NL

Clinical Prediction Models Book Review:

Prediction models are important in various fields, including medicine, physics, meteorology, and finance. Prediction models will become more relevant in the medical field with the increase in knowledge on potential predictors of outcome, e.g. from genetics. Also, the number of applications will increase, e.g. with targeted early detection of disease, and individualized approaches to diagnostic testing and treatment. The current era of evidence-based medicine asks for an individualized approach to medical decision-making. Evidence-based medicine has a central place for meta-analysis to summarize results from randomized controlled trials; similarly prediction models may summarize the effects of predictors to provide individu- ized predictions of a diagnostic or prognostic outcome. Why Read This Book? My motivation for working on this book stems primarily from the fact that the development and applications of prediction models are often suboptimal in medical publications. With this book I hope to contribute to better understanding of relevant issues and give practical advice on better modelling strategies than are nowadays widely used. Issues include: (a) Better predictive modelling is sometimes easily possible; e.g. a large data set with high quality data is available, but all continuous predictors are dich- omized, which is known to have several disadvantages.

Financial Risk Management

Financial Risk Management
Author: Jimmy Skoglund,Wei Chen
Publsiher: John Wiley & Sons
Total Pages: 576
Release: 2015-09-08
ISBN 10: 1119157242
ISBN 13: 9781119157243
Language: EN, FR, DE, ES & NL

Financial Risk Management Book Review:

A global banking risk management guide geared toward the practitioner Financial Risk Management presents an in-depth look at banking risk on a global scale, including comprehensive examination of the U.S. Comprehensive Capital Analysis and Review, and the European Banking Authority stress tests. Written by the leaders of global banking risk products and management at SAS, this book provides the most up-to-date information and expert insight into real risk management. The discussion begins with an overview of methods for computing and managing a variety of risk, then moves into a review of the economic foundation of modern risk management and the growing importance of model risk management. Market risk, portfolio credit risk, counterparty credit risk, liquidity risk, profitability analysis, stress testing, and others are dissected and examined, arming you with the strategies you need to construct a robust risk management system. The book takes readers through a journey from basic market risk analysis to major recent advances in all financial risk disciplines seen in the banking industry. The quantitative methodologies are developed with ample business case discussions and examples illustrating how they are used in practice. Chapters devoted to firmwide risk and stress testing cross reference the different methodologies developed for the specific risk areas and explain how they work together at firmwide level. Since risk regulations have driven a lot of the recent practices, the book also relates to the current global regulations in the financial risk areas. Risk management is one of the fastest growing segments of the banking industry, fueled by banks' fundamental intermediary role in the global economy and the industry's profit-driven increase in risk-seeking behavior. This book is the product of the authors' experience in developing and implementing risk analytics in banks around the globe, giving you a comprehensive, quantitative-oriented risk management guide specifically for the practitioner. Compute and manage market, credit, asset, and liability risk Perform macroeconomic stress testing and act on the results Get up to date on regulatory practices and model risk management Examine the structure and construction of financial risk systems Delve into funds transfer pricing, profitability analysis, and more Quantitative capability is increasing with lightning speed, both methodologically and technologically. Risk professionals must keep pace with the changes, and exploit every tool at their disposal. Financial Risk Management is the practitioner's guide to anticipating, mitigating, and preventing risk in the modern banking industry.

Credit Risk Modelling

Credit Risk Modelling
Author: David Jamieson Bolder
Publsiher: Springer
Total Pages: 684
Release: 2018-10-31
ISBN 10: 3319946889
ISBN 13: 9783319946887
Language: EN, FR, DE, ES & NL

Credit Risk Modelling Book Review:

The risk of counterparty default in banking, insurance, institutional, and pension-fund portfolios is an area of ongoing and increasing importance for finance practitioners. It is, unfortunately, a topic with a high degree of technical complexity. Addressing this challenge, this book provides a comprehensive and attainable mathematical and statistical discussion of a broad range of existing default-risk models. Model description and derivation, however, is only part of the story. Through use of exhaustive practical examples and extensive code illustrations in the Python programming language, this work also explicitly shows the reader how these models are implemented. Bringing these complex approaches to life by combining the technical details with actual real-life Python code reduces the burden of model complexity and enhances accessibility to this decidedly specialized field of study. The entire work is also liberally supplemented with model-diagnostic, calibration, and parameter-estimation techniques to assist the quantitative analyst in day-to-day implementation as well as in mitigating model risk. Written by an active and experienced practitioner, it is an invaluable learning resource and reference text for financial-risk practitioners and an excellent source for advanced undergraduate and graduate students seeking to acquire knowledge of the key elements of this discipline.

Developing Credit Risk Models Using SAS Enterprise Miner and SAS STAT

Developing Credit Risk Models Using SAS Enterprise Miner and SAS STAT
Author: Iain Brown
Publsiher: Unknown
Total Pages: 174
Release: 2019-07-03
ISBN 10: 9781642953152
ISBN 13: 1642953156
Language: EN, FR, DE, ES & NL

Developing Credit Risk Models Using SAS Enterprise Miner and SAS STAT Book Review:

Combine complex concepts facing the financial sector with the software toolsets available to analysts. The credit decisions you make are dependent on the data, models, and tools that you use to determine them. Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications combines both theoretical explanation and practical applications to define as well as demonstrate how you can build credit risk models using SAS Enterprise Miner and SAS/STAT and apply them into practice. The ultimate goal of credit risk is to reduce losses through better and more reliable credit decisions that can be developed and deployed quickly. In this example-driven book, Dr. Brown breaks down the required modeling steps and details how this would be achieved through the implementation of SAS Enterprise Miner and SAS/STAT. Users will solve real-world risk problems as well as comprehensively walk through model development while addressing key concepts in credit risk modeling. The book is aimed at credit risk analysts in retail banking, but its applications apply to risk modeling outside of the retail banking sphere. Those who would benefit from this book include credit risk analysts and managers alike, as well as analysts working in fraud, Basel compliancy, and marketing analytics. It is targeted for intermediate users with a specific business focus and some programming background is required. Efficient and effective management of the entire credit risk model lifecycle process enables you to make better credit decisions. Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications demonstrates how practitioners can more accurately develop credit risk models as well as implement them in a timely fashion.

Python Data Science Handbook

Python Data Science Handbook
Author: Jake VanderPlas
Publsiher: "O'Reilly Media, Inc."
Total Pages: 548
Release: 2016-11-21
ISBN 10: 1491912138
ISBN 13: 9781491912133
Language: EN, FR, DE, ES & NL

Python Data Science Handbook Book Review:

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

Modeling of Transport Demand

Modeling of Transport Demand
Author: V.A Profillidis,G.N. Botzoris
Publsiher: Elsevier
Total Pages: 500
Release: 2018-10-23
ISBN 10: 0128115149
ISBN 13: 9780128115145
Language: EN, FR, DE, ES & NL

Modeling of Transport Demand Book Review:

Modeling of Transport Demand explains the mechanisms of transport demand, from analysis to calculation and forecasting. Packed with strategies for forecasting future demand for all transport modes, the book helps readers assess the validity and accuracy of demand forecasts. Forecasting and evaluating transport demand is an essential task of transport professionals and researchers that affects the design, extension, operation, and maintenance of all transport infrastructures. Accurate demand forecasts are necessary for companies and government entities when planning future fleet size, human resource needs, revenues, expenses, and budgets. The operational and planning skills provided in Modeling of Transport Demand help readers solve the problems they face on a daily basis. Modeling of Transport Demand is written for researchers, professionals, undergraduate and graduate students at every stage in their careers, from novice to expert. The book assists those tasked with constructing qualitative models (based on executive judgment, Delphi, scenario writing, survey methods) or quantitative ones (based on statistical, time series, econometric, gravity, artificial neural network, and fuzzy methods) in choosing the most suitable solution for all types of transport applications. Presents the most recent and relevant findings and research - both at theoretical and practical levels - of transport demand Provides a theoretical analysis and formulations that are clearly presented for ease of understanding Covers analysis for all modes of transportation Includes case studies that present the most appropriate formulas and methods for finding solutions and evaluating results

Science and Judgment in Risk Assessment

Science and Judgment in Risk Assessment
Author: National Research Council,Division on Earth and Life Studies,Board on Environmental Studies and Toxicology,Commission on Life Sciences,Committee on Risk Assessment of Hazardous Air Pollutants
Publsiher: National Academies Press
Total Pages: 672
Release: 1994-01-01
ISBN 10: 030904894X
ISBN 13: 9780309048941
Language: EN, FR, DE, ES & NL

Science and Judgment in Risk Assessment Book Review:

The public depends on competent risk assessment from the federal government and the scientific community to grapple with the threat of pollution. When risk reports turn out to be overblown--or when risks are overlooked--public skepticism abounds. This comprehensive and readable book explores how the U.S. Environmental Protection Agency (EPA) can improve its risk assessment practices, with a focus on implementation of the 1990 Clean Air Act Amendments. With a wealth of detailed information, pertinent examples, and revealing analysis, the volume explores the "default option" and other basic concepts. It offers two views of EPA operations: The first examines how EPA currently assesses exposure to hazardous air pollutants, evaluates the toxicity of a substance, and characterizes the risk to the public. The second, more holistic, view explores how EPA can improve in several critical areas of risk assessment by focusing on cross-cutting themes and incorporating more scientific judgment. This comprehensive volume will be important to the EPA and other agencies, risk managers, environmental advocates, scientists, faculty, students, and concerned individuals.

Operational Risk Capital Models

Operational Risk Capital Models
Author: Rafael Cavestany,Brenda Boultwood,Laureano F. Escudero
Publsiher: Unknown
Total Pages: 459
Release: 2015
ISBN 10: 9781782722014
ISBN 13: 1782722017
Language: EN, FR, DE, ES & NL

Operational Risk Capital Models Book Review:

"Operational Risk Capital Models is a guide for the implementation of state of the art operational risk capital models suitable for regulatory approval. For insurers, Solvency II implementation has created the need, in both highly developed and less developed markets, for the development of these models that help to better understand risks, safe capital and compliance. For the banking industry, regulators in many countries in Africa, Asia and Latin America (as well as Europe) are pressing their local banks to implement advanced operational risk capital models. Banks that have made early implementation are looking to improve their capital models with new advances to match the increasing regulatory requirements. Operational Risk Capital Models enables you to model your operational risk capital to ensure the model meets regulatory standards. It describes the process end to end, from the capture of the required data to the modelling and VaR calculation, as well as the integration of capital results into your institution's daily risk management." --Contratapa.

International Convergence of Capital Measurement and Capital Standards

International Convergence of Capital Measurement and Capital Standards
Author: Anonim
Publsiher: Lulu.com
Total Pages: 239
Release: 2004
ISBN 10: 9291316695
ISBN 13: 9789291316694
Language: EN, FR, DE, ES & NL

International Convergence of Capital Measurement and Capital Standards Book Review: